Friday, August 19, 2011

"This 4T pixel, in a 0.18µm CMOS technology, has high fill factor and is compatible with frontside and backside illumination. The pixel has a very high charge to voltage conversion. In the present configuration we now demonstrate less than 0.5 electronsRMS read noise in the dark.

We will disclose more details on this proprietary technology at upcoming scientific conferences. We invite interested groups willing to provide independent confirmation of our results to contact us. Applications are in low noise and/or low light imaging, i.e. in virtually all imaging domains."

Another issue is the noise distribution form. For a CCD device, there is virtually no noise during the charge transfert and the thermal noise is injected at the CS amplifier stage. The noise distribution is very Gaussian.

But for CMOS image sensor, even with KTC cancelling in a 4T pixel, the operation is NOT noiseless. So the final noise distribution is more complexe and very often not Gaussian.

People states that 1.5 e readout noise gives equivalent image quality as 5 e readout noise in a CCD. Any comments on this issue ?

@ "People states that 1.5 e readout noise gives equivalent image quality as 5 e readout noise in a CCD. Any comments on this issue ?"

From what I've seen in my measurements of many modern CMOS sensors, the readout noise is quite close to Gaussian. Sometimes the digital black level is set so low that negative part of this Gaussian is partially cut, but still the histogram shows the recognizable Gaussian shape.

What is not Gaussian is the dark current distribution. I was told that in many CCDs it's narrower than in CMOS sensors.

I think that you talk about the temporel RMS noise of CMOS sensor. The fact is that if the pixel noise is stationnary, it will verify the ergodicity. So spatial noise distribution and temporel bruit distribution should be the same.

But if you take one dark image of CMOS sensor and calculate the noise distribution, you will not have the Guassian distribution. If you take a dark image from a good CCD, you will get the Gaussian distribution.

For observation purpose, your vision will take into account only few frames, so the spatial noise distribution plays a much more important role than the temporel RMS noise computed from, say, 50 consecutive frames for example.

Actually, I was talking about the total noise histogram, including both temporal and FPN noises across the whole frame. I have to say that my measurements were limited by small pixel sensors for camera phones. What I can tell that modern sensors from reputable companies tend to produce quite Gaussian-looking histograms (for short exposures). All sorts of outlying pixels are normally concealed by on-chip circuitry, so the end used does not see them and frames look clean and nice.

For long exposures the dark current component is clearly non-Gaussian, but for short exposures I do not significant deviations.

What is your experience? Do you see salt-and-pepper kind of noise or something else?

Micron MT9M001 CMOS in my QHY5 guide cam has a lot of fixed pattern noise. OmniVision CMOS devices from MS LifeCam HD webcmas tend to have much less noise (but also it's hard to tell as they are color sensors, and everything else I have is mono + with uncompressed output ;))